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Embedding LLM Circuit Breakers Into AI Might Save Us From A Whole Lot Of Ghastly Troubles

Jan 15, 2025 - forbes.com
The article discusses the emerging trend of embedding specialized circuit breakers within generative AI and large language models (LLMs) to prevent undesirable outcomes, such as AI producing harmful content or engaging in dangerous activities. These AI circuit breakers function similarly to electrical circuit breakers by interrupting processes that could lead to negative consequences. They can be implemented at different stages of AI processing: upon receiving input, during processing, or just before output. There are two main types of AI circuit breakers: language-level, which is easier to implement but can be circumvented, and representation-level, which is more complex and harder to bypass.

The article highlights the importance of AI circuit breakers in maintaining AI alignment with human values and preventing misuse or unintended harmful actions. It provides examples of how these circuit breakers can be activated at various stages of AI processing to block inappropriate requests. The piece also references ongoing research in the field, emphasizing the need for robust AI cybersecurity measures, especially with the rise of agentic AI. Overall, AI circuit breakers are portrayed as a crucial tool in ensuring the safe and ethical deployment of AI technologies.

Key takeaways:

  • AI circuit breakers are being embedded in generative AI and large language models to prevent harmful outputs and ensure AI alignment with human values.
  • There are two main types of AI circuit breakers: language-level, which detects issues based on words or tokens, and representation-level, which operates at a deeper computational level.
  • AI circuit breakers can be activated at different stages of AI processing: upon input, during processing, or just before output, to prevent undesirable responses.
  • Research and development of representation-level AI circuit breakers are ongoing, aiming to enhance AI cybersecurity and prevent adversarial attacks.
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